An iterated local search algorithm for the permutation flowshop problem with total flowtime criterion

Dong, Xianguang; Huang, Houkuan; Chen, Ping

doi:10.1016/j.cor.2008.04.001

Cited by 109 publications

(62 citation statements)

References 37 publications

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“…Several acceptance criteria have been compared; the best performing was ConstTemp, which corresponds to choosing a constant temperature in the LSMC criterion. This ILS algorithm was shown to be among the top performing metaheuristic algorithms for the PFSP [76]; an adaptation of this ILS algorithm has also shown very good performance on the flow shop problem with flowtime objective [27]. The ILS algorithm has also been extended to an iterated greedy (IG) algorithm [77].…”

Section: Ils For Other Problemsmentioning

confidence: 99%

Iterated Local Search: Framework and Applications

Lourenço

Martin

Stützle

2010

International Series in Operations Research &Amp; Management Science

371

262

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Section: Ils For Other Problemsmentioning

confidence: 99%

Iterated Local Search: Framework and Applications

Lourenço

Martin

Stützle

2010

International Series in Operations Research &Amp; Management Science

371

262

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“…In any case, our proposed methods are arguably simpler than most others and still attain the best performance. The superiority of the presented algorithms and the ILS D of Dong et al (2009) demonstrates the effectiveness of simple local search frameworks. Together with the fact that local search also plays a significant role in most high performing methods, we conclude that a well designed local search based algorithm is all that is needed in order to obtain state-of-the-art results for the problem considered without turning into more complex methods such as genetic or estimation of distribution algorithms.…”

mentioning

confidence: 99%

Local search methods for the flowshop scheduling problem with flowtime minimization

Pan

Ruíz

2012

European Journal of Operational Research

121

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Flowshop scheduling is a very active research area. This problem still attracts a considerable amount of interest despite the sheer amount of available results. Total flowtime minimization of a flowshop has been actively studied and many effective algorithms have been proposed in the last few years. New best solutions have been found for common benchmarks at a rapid pace. However, these improvements many times come at the cost of sophisticated algorithms. Complex methods hinder potential applications and are difficult to extend to small problem variations. Replicability of results is also a challenge. In this paper, we examine simple and easy to implement methods that at the same time result in state-of-the-art performance. The first two proposed methods are based on the well known Iterated Local Search (ILS) and Iterated Greedy (IG) frameworks, which have been applied with great success to other flowshop problems. Additionally, we present extensions of these methods that work over populations, something that we refer to as population-based ILS (pILS) and population-based IG (pIGA), respectively. We calibrate the presented algorithms by means of the Design of Experiments (DOE) approach. Extensive comparative evaluations are carried out against the most recent techniques for the considered problem in the literature. The results of a comprehensive computational and statistical analysis show that the presented algorithms are very effective. Furthermore, we show that, despite their simplicity, the presented methods are able to improve 12 out of 120 best known solutions of Taillard's flowshop benchmark with total flowtime criterion.

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“…When using local search methods, an intensive exploration of the solution space is performed by moving at each step from the current solution to another promising solution in its neighbors [12]. The proposed MRSILS removes a node and reinserts it to the best location according to SDVRP constraints.…”

Section: Discussionmentioning

confidence: 99%

An Iterated Local Search for the Split Delivery Vehicle Routing Problem

Wen¹,

Dong²,

Han³

2015

Proceedings of the International Conference on Computer Information Systems and Industrial Applications

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Abstract--A multi-restart iterated local search (MRSILS) algorithm is introduced for the Split Delivery Vehicle Routing Problem (SDVRP). The initial solution is generated by the GENIUS and applied the local search procedure by removing one node from its current route and inserting it into the best locations, with the possibility of splitting its demand. A node inserting algorithm is proposed for SDVRP, trying to find a better solution by an insertion with the consideration of splitting the demand. The perturbation is applied while certain predefined continuous no improvement local search steps are occurred. In order to extend the search space and keeping the quality of the restart solution, a method is designed for the perturbation that the perturbed solution is chosen from an elite solution set, while the best solution is preferred. The object of this work is to minimize the total travel distance. Experimental results on a benchmark set show that the MRSILS is competitive with a state of the art algorithm.

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An iterated local search algorithm for the permutation flowshop problem with total flowtime criterion

Cited by 109 publications

References 37 publications

Iterated Local Search: Framework and Applications

Iterated Local Search: Framework and Applications

Local search methods for the flowshop scheduling problem with flowtime minimization

An Iterated Local Search for the Split Delivery Vehicle Routing Problem

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